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AI Success Demands 4x More Investment in Core Data & Talent

Technology companies with successful AI initiatives invest up to four times more in foundational capabilities like data quality and AI-ready talent. According to a Gartner report, only 39% of technology leaders are confident of seeing positive financial returns from their AI investments. The report outlines six key shifts needed to realize AI value, including building AI-first data capabilities and strengthening governance models. Organizations with advanced data and analytics capabilities are achieving up to 65% higher business outcomes, such as revenue growth and cost optimization.

Key Points: AI Investment: 4x More in Core Capabilities for 39% ROI

  • Invest 4x more in data & talent for AI success
  • Only 39% of leaders see positive AI returns
  • Advanced capabilities yield 65% better outcomes
  • Trust in data is fundamental for AI value
  • Shift from ROI to long-term value creation
2 min read

AI firms invest 4 times more in core capabilities, leaders see 39 pc returns: Report

Gartner report reveals AI leaders invest 4x more in data, talent & governance, yet only 39% see positive returns. Key shifts for AI value outlined.

"Without trust in the data, outputs and decisions of AI models, there is no value from AI. - Rita Sallam, Gartner"

New Delhi, April 20

Technology companies with successful artificial intelligence initiatives invest up to four times more in core capabilities such as data quality, governance, AI-ready talent and change management, even as only 39 per cent of technology leaders are confident of seeing positive financial returns from their AI investments, a report said on Monday.

According to a report by Gartner, higher investments in foundational areas play a critical role in driving AI success across enterprises.

The report has outlined six key shifts needed to realise AI value, including building AI-first data and analytics capabilities, redesigning teams for human and AI collaboration, and strengthening context and data infrastructure to support AI systems.

It also highlighted the need for integrated engineering practices, trust-based governance models and a move beyond traditional return on investment (ROI) metrics towards long-term value creation.

"Organisations with advanced AI-ready data and analytics capabilities are achieving up to 65 per cent higher business outcomes, including revenue growth and cost optimisation," Gartner said.

"D&A leaders play a central role in achieving their organisation's AI value ambition," said Rita Sallam, Distinguished VP Analyst, Gartner Fellow and Chief of Research at Gartner.

Sallam noted that through 2030, the mandate for D&A leaders will be to build strong foundational capabilities, including trusted data and context-driven intelligence, requiring shifts in how teams operate, scale and create value.

However, challenges remain. Only 23 per cent of IT leaders are highly confident in their organisation's ability to manage security and governance while deploying generative AI tools.

"Without trust in the data, outputs and decisions of AI models, there is no value from AI," Sallam said.

Earlier, another report flagged that tech firms accelerated job cuts in the first quarter of 2026, with over 73,200 layoffs by 95 companies.

It pointed out that within two weeks, Snap Inc., The Walt Disney Company, Meta Platforms and Oracle Corporation announced layoffs as firms streamline operations to cut costs and shift resources toward artificial intelligence.

- IANS

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Reader Comments

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Priya S
Only 39% confident of returns? That's a sobering number. It shows AI implementation is harder than it looks. The focus on "AI-ready talent" is crucial. We need proper training programs in our colleges and companies, not just theoretical knowledge.
R
Rohit P
The link between layoffs and AI resource shift is worrying. Are we automating jobs without a clear plan for the workforce? Companies need a responsible transition strategy. Upskilling is non-negotiable. 🤔
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Sarah B
"Without trust in the data, there is no value from AI." - This single line sums up the entire challenge. Garbage in, garbage out. This applies doubly in India where data collection practices can be... inconsistent. Governance models are key.
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Vikram M
The 65% higher business outcomes stat is impressive, but it requires 4x investment first. That's a huge upfront cost. For MSMEs in India, this creates a big divide. Hope government schemes can help bridge this AI readiness gap.
K
Karthik V
Respectfully, while the report highlights necessary shifts, it feels like it's stating the obvious for anyone in the tech field. The real insight would be *how* to achieve these shifts practically, especially in cost-sensitive markets like India. The "what" is clear, the "how" is the billion-dollar question.
M

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